import pandas as pd
import plotly.express as px
from IPython.display import display
from lib import load_adi_all_states, us_adi_zip5_stats, draw_us_adi_distribution, draw_adi_map
us_adi = load_adi_all_states(False)
draw_us_adi_distribution(us_adi)
adi_stats = us_adi_zip5_stats(us_adi)
display(adi_stats)
draw_adi_map(adi_stats)
| _state | _zip5 | count | min | max | adi_mean | std | _lat | _lng | _census_total | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | AK | 99501 | 2988 | 7.0 | 97.0 | 33.152276 | 18.076871 | 61.219998 | -149.857840 | 17603 |
| 1 | AK | 99502 | 2745 | 11.0 | 43.0 | 24.122404 | 8.677508 | 61.163652 | -149.996643 | 24168 |
| 2 | AK | 99503 | 2524 | 10.0 | 72.0 | 39.593502 | 8.925617 | 62.043689 | -158.174466 | 14563 |
| 3 | AK | 99504 | 3420 | 19.0 | 98.0 | 36.341228 | 16.996213 | 61.190578 | -149.607154 | 40914 |
| 4 | AK | 99505 | 1020 | 31.0 | 31.0 | 31.000000 | 0.000000 | 61.284745 | -149.653973 | 6174 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 31741 | WY | 83124 | 267 | 38.0 | 74.0 | 48.921348 | 16.580783 | 41.758808 | -110.315880 | 137 |
| 31742 | WY | 83126 | 281 | 33.0 | 33.0 | 33.000000 | 0.000000 | 42.581108 | -110.904209 | 334 |
| 31743 | WY | 83127 | 1689 | 27.0 | 39.0 | 36.278863 | 4.083667 | 42.918972 | -110.997753 | 3041 |
| 31744 | WY | 83128 | 892 | 23.0 | 44.0 | 42.233184 | 5.224854 | 43.040079 | -110.722208 | 1601 |
| 31745 | WY | 83414 | 111 | 3.0 | 22.0 | 3.171171 | 1.803400 | 43.861439 | -110.935725 | 544 |
31530 rows × 10 columns